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Analysis of the Spatiotemporal Variation Characteristics and Driving Factors of Land Vegetation GPP in a Certain Region of Asia

DOI: 10.4236/oje.2024.146030, PP. 523-543

Keywords: Gross Primary Productivity, Spatiotemporal Variations, Model, Driving Factors

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Abstract:

Gross primary productivity (GPP) of vegetation is a critical indicator of ecosystem growth and carbon sequestration. The spatiotemporal variation characteristics of land vegetation GPP trends in a specific region of Asia from 2001 to 2020 were analyzed by Sen and MK trend analysis methods in this study .Moreover , a GPP change attribution model was established to explore the driving influences of factors such as Leaf Area Index (LAI), Land Surface Temperature (LST), Vapor Pressure Deficit (VPD), Soil Moisture, Solar Radiation and Wind Speed on GPP. The results indicate that summer GPP values are significantly higher than those in other months, accounting for 60.8% of the annual total GPP; spring and autumn contribute 18.91% and 13.04%, respectively. In winter, due to vegetation being nearly dormant, the contribution is minimal at 7.19%. Spatially, GPP shows a decreasing trend from southeast to northwest. LAI primarily drives the spatial and seasonal variations of regional GPP, while VPD, surface temperature, solar radiation, and soil moisture have varying impacts on GPP across different dimensions. Additionally, wind speed exhibits a minor contribution to GPP across different dimensions.

References

[1]  Forzieri, G., Alkama, R., Miralles, D.G., et al. (2017) Satellites Reveal Contrasting Responses of Regional Climate to the Widespread Greening of Earth. Science (American Association for the Advancement of Science), 356, 1180-1184.
https://doi.org/10.1126/science.aal1727
[2]  Melillo, J.M., McGuire, A.D., Kicklighter, D.W., et al. (1993) Global Climate Change and Terrestrial Net Primary Production. Nature, 363, 234-240.
https://doi.org/10.1038/363234a0
[3]  Diffenbaugh, N.S. and Burke, M. (2019) Global Warming Has Increased Global Economic Inequality. Proceedings of the National Academy of Sciences, 116, 9808-9813.
https://doi.org/10.1073/pnas.1816020116
[4]  Li, X., Liang, S., Yu, G., et al. (2013) Estimation of Gross Primary Production over the Terrestrial Ecosystems in China. Ecological Modelling, 261-262, 80-92.
https://doi.org/10.1016/j.ecolmodel.2013.03.024
[5]  Zhou, S. (2017) Study on the Potential Water Use Efficiency Model of Terrestrial Ecosystems and Its Application. Ph.D. Thesis, Tsinghua University. (In Chinese)
[6]  Zhu, X., Zhang, S., Liu, T., et al. (2021) Impacts of Heat and Drought on Gross Primary Productivity in China. Remote Sensing, 13, Article 378.
https://doi.org/10.3390/rs13030378
[7]  Beer, C., et al. (2010) Terrestrial Gross Carbon Dioxide Uptake: Global Distribution and Covariation with Climate. Science, 329, 834-838.
https://doi.org/10.1126/science.1184984
[8]  Xia, Z. (2024) The Spatiotemporal Variation of Terrestrial Vegetation Phenology and Its Driving Factors in the Sanjiangyuan Region. Master’s Thesis, Qinghai University. (In Chinese)
[9]  Zhang, X.D., Ding, L.R., Zhou, J., et al. (2023) Daily 1km All-Weather Land Surface Temperature Dataset for China’s Land and Surrounding Areas (TRIMS LST; 2000-2022). National Tibetan Plateau Data Center. National Tibetan Plateau Data Center.
https://doi.org/10.11888/Meteoro.tpdc.271252
[10]  Shao, C.K., Jiang, Y.Z., Yang, K., et al. (2023) Long-Term High-Resolution Ground Meteorological Forcing Dataset for the Third Pole Region (TPMFD, 1979-2022). National Tibetan Plateau Data Center. National Tibetan Plateau Data Center.
https://doi.org/10.11888/Atmos.tpdc.300398
[11]  Shangguan, Y.L., Shi, Z. and Min, X.X. (2023) Daily 1km Soil Moisture Dataset of the Tibetan Plateau (2001-2020). National Tibetan Plateau Data Center. National Tibetan Plateau Data Center.
https://doi.org/10.11888/Terre.tpdc.300224
[12]  Gu, C.J., Zhang, Y.L., Liu, L.S., et al. (2023) Consistency Assessment of Four NDVI Datasets in the Sanjiangyuan Region of Qinghai. Geographical Research, 42, 1378-1392.
[13]  Liu, C. (2022) Study on the Impact of Vegetation Restoration on Soil Moisture in the Loess Plateau. Master’s Thesis, Hebei GEO University.
[14]  Tian, Z.H., Ren, Z.G. and Wei, H.T. (2022) Driving Mechanisms of Vegetation Spatiotemporal Evolution in the Yellow River Basin from 2000 to 2020. Environmental Science, 43, 743-751.
https://doi.org/10.13227/j.hjkx.202105213

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